Performance Analysis of Machine Learning Algorithms on Small Datasets that Includes Features from K-Nearest Neighbor Graph
Date Issued
2023-07
Author(s)
Ilievska, Elena
Sekuloski, Petar
Abstract
Modern technology in today’s world is largely driven by machine learning algorithms. They are incorporated into every field. Big data is not always available to us, though. We frequently have to work with limited-size of data. The purpose of this paper is to demonstrate several machine learning algorithms and their accuracy on small numerical datasets. We investigate the effectiveness of these algorithms with and without the implementation of two variables, degree and closeness centrality, which are extracted from the dataset using the knearest neighbor graph.
Subjects
File(s)![Thumbnail Image]()
Loading...
Name
CIIT2023_paper_34.pdf
Size
8.97 MB
Format
Adobe PDF
Checksum
(MD5):05b52ecb5b4e027bbf3419336d8f22aa